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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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schemes prioritised over others? What mechanisms exist to evaluate whether schemes are successful (or not)? What lessons can be learned from existing schemes locally and elsewhere to improve outcomes
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the National Physical Laboratory (NPL) and Waters-TA Instruments, this project will investigate key measurement techniques, such as thermal analysis, rheology, and mechanical testing, to characterise
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computing and analysis of data will enable the development of control mechanisms that will overcome one of the major barriers for exploiting the benefits of hybrid propellant propulsion systems. The project
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the Leverhulme Trust and supervised by Dr Fraser Smith , Dr Stephanie Rossit (UEA) and Professor Tim Kietzmann (University Osnabruck, Germany). The project will determine the neural and computational mechanisms
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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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to study corrosion, cracking and mechanical degradation, develop advanced computational models using modern C++ and high-performance computing to simulate material behaviour over a 100+ year timespan. This
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degree in Electrical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field, with a genuine interest in Wearable Technology, Sensor Development, Biomedical Devices, and Data
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to Apply: Apply online via the above ‘Apply’ button. Under programme name, select ‘Mechanical and Manufacturing Engineering’ and quote the advert reference number ‘PARAFIT-TS-25’ under the ‘Finance’ section